Researcher, University of Žilina, Slovakia
Dr. Peter Klčo is a skilled scientific researcher specializing in biomedical engineering, machine learning, and neural networks. His expertise spans a wide range of topics, from signal processing and cough monitoring to machine learning applications for object detection and timeseries prediction. His dedication to advancing the field is reflected in his successful research projects and numerous contributions to scientific literature. Dr. Klčo is currently serving as a scientific researcher at the University of Žilina, Faculty of Electrical Engineering and Information Technology, where his work in artificial intelligence and its application to practical engineering solutions has garnered significant recognition. 🧑🔬🔬
Profile
Scopus
Education
Dr. Klčo earned his PhD in biomedical engineering from Jessenius Faculty of Medicine, Comenius University in Bratislava, where he focused on the ambulatory monitoring of coughs in his dissertation. Before that, he completed his MSc in Biomedical Engineering at the Faculty of Electrical Engineering, University of Žilina. His academic journey provided him with a strong foundation in both engineering and healthcare, forming the basis for his multidisciplinary research. 🎓📚
Experience
Dr. Klčo’s career spans across various roles, starting as a freelance programmer and research assistant at the Jessenius Faculty. He later worked as a C Embedded Programmer at Globallogic Žilina and a PhD researcher at the Jessenius Faculty. Since October 2020, he has been a scientific researcher at the University of Žilina. His contributions include successful transfer learning projects in fields such as energy consumption prediction and automated detection of defects in PCB boards. 💼💻
Research Interest
Dr. Klčo’s research interests are vast, focusing primarily on machine learning applications in engineering and biomedical fields. His work includes neural networks for timeseries forecasting, object detection (such as soldering splashes and road potholes), and the development of models for energy systems and photovoltaic control. He also continues his research in medical applications, notably cough sound classification using artificial intelligence techniques. 🧠🔍
Awards
Dr. Klčo has been recognized for his innovative research contributions, with his work being published in numerous prestigious journals and presented at international conferences. His continuous commitment to advancing machine learning applications, especially in real-time systems and sensor technologies, positions him as a leading researcher in his field. 🏆📈
Publications Top Notes
Dr. Klčo has an extensive list of published works. Some of his most notable publications include:
Klčo, P., Koniar, D., Hargaš, L., & Paškala, M. (2024). Comparison of Preprocessing Methods Impact on Detection of Soldering Splashes Using Different YOLOv8 Versions.
Klčo, P., Simonova, A., Koniar, D., & Hargas, L. (2024). Quaternion Neural Network in Application of MPPT Controller.
Klčo, P., Koniar, D., Hargas, L., Pociskova Dimova, K., & Chnapko, M. (2023). Quality inspection of specific electronic boards by deep neural networks. Scientific Reports, 13(1), 20657.
Klčo, P., Koniar, D., Hargas, L., & Paskala, M. (2023). Automated Detection of Potholes Using YOLOv5 Neural Network. Transportation Research Procedia, 74, 1150-1155.
Klčo, P., Koniar, D., Hargas, L., & Paskala, M. (2022). Automated detection of soldering splashes using YOLOv5 algorithm. In 2022 International Conference on Applied Electronics (AE).
Morgoš J, Klčo P, Hrudkay K. (2022). Artificial neural network based MPPT algorithm for modern household with electric vehicle. Communications, University of Žilina.
Klčo P, Kollárik M, Tatár M. (2018). Novel computer algorithm for cough monitoring based on octonions. Respiratory Physiology & Neurobiology, 257, 36-41.
Klčo P, Smetana M, Kollárik M, Tatár M. (2017). Application of Octonions in the Cough Sounds Classification. Advances in Applied Science Research, 8(2), 30-37.